Overview of Multidimensional Modeling and Calculations in Analysis Services

Microsoft SQL Server Analysis Services (SSAS) provides a powerful platform for building business intelligence solutions. Multidimensional modeling is a core component of SSAS, allowing you to design cubes that represent business data in a way that is intuitive and efficient for analysis and reporting. Calculations within these cubes are essential for deriving meaningful insights and answering complex business questions.

Understanding Multidimensional Models

A multidimensional model in Analysis Services is built around the concept of a cube. A cube is a data structure that aggregates data from a relational data source (like a data warehouse or operational database) into a multidimensional space. The key components of a multidimensional model include:

  • Measures: These are the quantitative values that you want to analyze, such as Sales Amount, Quantity Sold, or Profit. Measures are typically numeric and are aggregated using functions like SUM, COUNT, AVERAGE, MIN, or MAX.
  • Dimensions: These represent the business perspectives through which you analyze your measures. Common dimensions include Time, Geography, Product, and Customer. Dimensions contain hierarchies that allow users to drill down and roll up data.
  • Hierarchies: Within dimensions, hierarchies represent levels of granularity. For example, a Time dimension might have a hierarchy of Year -> Quarter -> Month -> Day.
  • Cubes: A cube is formed by combining measures and dimensions. It provides a structure for multidimensional analysis.
  • Schemas: A schema is a collection of related cubes and their associated dimensions.

The Role of Calculations

While raw measures provide fundamental insights, business users often need more complex calculations to understand trends, perform "what-if" analysis, and gain deeper insights. Analysis Services supports two primary types of calculations:

1. Basic Aggregations (Implicit Calculations)

When you define measures, Analysis Services automatically provides basic aggregation capabilities based on the chosen aggregation function (e.g., SUM, COUNT). These are the fundamental building blocks of your analysis.

2. Calculated Measures and Calculated Members (Explicit Calculations)

These are user-defined calculations that go beyond simple aggregation. They are typically written using Multidimensional Expressions (MDX).

  • Calculated Measures: These are measures defined at the cube level and appear alongside regular measures in reporting tools. They can perform calculations based on existing measures. For example, a "Profit Margin" calculated measure might be defined as [Profit] / [Sales Amount].
  • Calculated Members: These are members defined within a dimension hierarchy. They allow you to create custom groupings, time-based calculations, or scenario comparisons within a dimension. For instance, you could create a "Previous Year Sales" calculated member in a Time dimension.

Multidimensional Expressions (MDX)

MDX is a query language specifically designed for querying multidimensional data sources. It is the primary language used to define calculated measures and calculated members in Analysis Services. MDX provides a rich set of functions for performing complex calculations, including:

  • Mathematical and statistical functions
  • Time-intelligence functions (e.g., calculating year-to-date totals, previous period values)
  • String manipulation functions
  • Set-based operations

A simple example of an MDX calculated measure for Profit Margin could look like this: 

CREATE MEMBER CURRENTCUBE.[Measures].[Profit Margin] AS
    ([Measures].[Profit] / [Measures].[Sales Amount]),
FORMAT_STRING = '0.00%'

Benefits of Multidimensional Modeling and Calculations

  • Performance: Pre-aggregated data and optimized structures lead to fast query responses, even with large datasets.
  • Ease of Use: Business users can analyze data through intuitive dimensions and hierarchies without needing direct access to the underlying relational tables.
  • Business Logic Encapsulation: Complex business rules and calculations are defined once in Analysis Services, ensuring consistency across all reporting tools.
  • Flexibility: MDX allows for the creation of dynamic and sophisticated analytical scenarios.

By mastering multidimensional modeling and the power of MDX calculations, you can empower your organization with robust and responsive business intelligence solutions.